Likelihood Ratio Order of m-Spacings in Multiple-Outlier Models

This article deals with the multiple-outlier exponential model. The likelihood ratio order between m-spacings of the combined sample is developed, some results extend the conclusions on simple spacings in Wen et al. (2007 Wen , S. , Lu , Q. , Hu , T. ( 2007 ). Likelihood ratio order of spacings of heterogeneous exponential random variables . J. Multivariate Anal. 98 : 743 – 756 .[Crossref], [Web of Science ®] , [Google Scholar]).     

Testing for the Equality of Two Autoregressive Functions Using Quasi-Residuals

This article discusses the problem of testing the equality of two nonparametric autoregressive functions against one-sided alternatives. The heteroscedastic errors and stationary densities of the two independent strong mixing strictly stationary time series can be possibly different. The article adapts the idea of using sum of quasi-residuals to construct the test and derives its asymptotic null distributions. The article also shows that the test is consistent for general alternatives and obtains its limiting distributions under a sequence of local alternatives. Then a Monte Carlo simulation is conducted to study the finite sample level and power behavior of these tests at some alternatives. We also compare the test to an existing lag matched test theoretically and by Monte Carlo experiments.     

Characterizations of the poisson process using,the variance

Let γ(t) be the residual life at time t of the renewal process {A(t), t > 0}, which has F as the common distribution function of the inter-arrival times. In this article we prove that if Var(γ(t)) is constant, then F will be exponentially or geometrically distributed under the assumption F is continuous or discrete respectively. An application and a related example also are given.     

Extreme Quantile Estimation for Autoregressive Models

ABSTRACT

A quantile autoregresive model is a useful extension of classical autoregresive models as it can capture the influences of conditioning variables on the location, scale, and shape of the response distribution. However, at the extreme tails, standard quantile autoregression estimator is often unstable due to data sparsity. In this article, assuming quantile autoregresive models, we develop a new estimator for extreme conditional quantiles of time series data based on extreme value theory. We build the connection between the second-order conditions for the autoregression coefficients and for the conditional quantile functions, and establish the asymptotic properties of the proposed estimator. The finite sample performance of the proposed method is illustrated through a simulation study and the analysis of U.S. retail gasoline price.     

Bayesian Proportional Hazard Analysis of the Timing of High School Dropout Decisions

In this paper, I study the timing of high school dropout decisions using data from High School and Beyond. I propose a Bayesian proportional hazard analysis framework that takes into account the specification of piecewise constant baseline hazard, the time-varying covariate of dropout eligibility, and individual, school, and state level random effects in the dropout hazard. I find that students who have reached their state compulsory school attendance ages are more likely to drop out of high school than those who have not reached compulsory school attendance ages. Regarding the school quality effects, a student is more likely to drop out of high school if the school she attends is associated with a higher pupil–teacher ratio or lower district expenditure per pupil. An interesting finding of the paper that comes along with the empirical results is that failure to account for the time-varying heterogeneity in the hazard, in this application, results in upward biases in the duration dependence estimates. Moreover, these upward biases are comparable in magnitude to the well-known downward biases in the duration dependence estimates when the modeling of the time-invariant heterogeneity in the hazard is absent.     

Bayesian Approaches to Nonparametric Estimation of Densities on the Unit Interval

This paper investigates nonparametric estimation of density on [0, 1]. The kernel estimator of density on [0, 1] has been found to be sensitive to both bandwidth and kernel. This paper proposes a unified Bayesian framework for choosing both the bandwidth and kernel function. In a simulation study, the Bayesian bandwidth estimator performed better than others, and kernel estimators were sensitive to the choice of the kernel and the shapes of the population densities on [0, 1]. The simulation and empirical results demonstrate that the methods proposed in this paper can improve the way the probability densities on [0, 1] are presently estimated.     

论统计泄露控制问题

一、背景统计泄露控制 (ＳｔａｔｉｓｔｉｃａｌＤｉｓｃｌｏｓｕｒｅＣｏｎｔｒｏｌ)是指统计部门在为社会提供的统计资料中 ,不泄露任一单个个体 (如住户 ,企业等 )的资料。这里有两层意思 ,一层是统计泄露的问题 ,另一层是控制方法的问题 ,两者是密不可分的。世界上有关统计泄露控制的研究已有 2 0多年的历史 ,有专门的人员、项目、机构来从事这个问题的研究。1 统计泄露控制的需求众所周知 ,统计部门对外公布的资料 ,基本上来说有两种 ,即汇总 (综合 )资料和微观资料 (调查单位原始资料 )。事实上 ,原始数据是汇总数据的原材料 ,在计算…     

士人与山川——从《容美纪游》看传统士人的山川观念

《容美纪游》是一本创作于清代康熙年间的游记作品,记录了作者顾彩在清康熙四十三年（1704年）前往湖北西部、今土家族分布区的容美土司地旅行五个多月的经历。顾彩心中的容美,既是野蛮地,又是桃花源,同时还是一个仙居地。顾彩对容美土司的三重印象,正是他应对自身所处时代的产物,寄托了他对理想社会的追求。顾彩的容美之旅,反映出以顾彩为代表的中国传统士人的一种山川观念。此类山川观念,实际是中国儒家士人中久存的一个传统。在＂士志于道＂的追寻中,山川之地成为了对自身社会的一个超越,成为一个＂求道＂之地。在现今鄂西地区的土家族历史或地方史研究中,《容美纪游》被视为唯一揭示清代改土归流之前鄂西地方政治、社会、地理历史面貌的史籍资料,因此有着极其重要的地位。     

“非遗”保护下花儿表演的实践调研——以第三届大通老爷山花儿会为例

花儿会作为一种特殊的民俗文化事项,它引起的社会群体联动效应日益彰显,尤其在当下"非遗"保护的大旗下,花儿会的作用为社会广泛关注,但是,花儿会生态的急剧变化已成为一种不容置疑的事实。本文以2012年6月青海大通举办的第三届老爷山花儿会为例,从政府作为、花儿生态的篡改、歌手和听众的关系、花儿群体的萎缩等方面,论述了"非遗"保护下花儿表演在当下的存活现状以及保护措施。